app3.py

#pip install --upgrade langchain_community
#pip install langchain_google_genai

import streamlit as st
from langchain_community.llms import OpenAI
#from langchain_community.llms import Gemini
#from langchain_google_gemini import Gemini 
from langchain_google_genai import ChatGoogleGenerativeAI


def main():
    st.title("Open AI or Gemini Options")

    # Radio
    st.header("Radio:")
    radio = st.radio("Radio", ["Open AI", "Gemini", "TBD"])  # Removed extra space after "Gemini"
    st.write("Selected option:", radio)
    role = st.text_input("Enter Role")
    st.write("Entered role:", role)   
        
    # Slider
    st.header("Slider:")
    temp = st.slider("Temperature", min_value=0.0, max_value=1.0, value=0.7, step=0.1)  # Corrected slider label
    st.write("Selected value:", temp)

    # Topic
    with st.form("my_form"):
        topic = st.text_area("Enter the topic for your LinkedIn post:")
        submitted = st.form_submit_button("Generate Post")
        if submitted and topic:
           # if radio == "Open AI":  # Corrected if statement syntax and comparison
            #generate_openai_post(role, temp)
            post = generate_linkedin_post(topic, role,temp,radio)
            st.info(post)
        elif submitted and not topic:
            st.error("Please enter a topic to generate a post.")

    def generate_linkedin_post(topic, role,temp,radio):
        # Enhanced prompt with additional context for better post generation
        prompt = (
            f"You as {role} Create a professional, engaging LinkedIn post about {topic}. "
            f"Adjust the tone and style based on a temperature of {temp}. " 
            "It should start with an attention grabbing hook based on audience pain. "
            "Then a line to agitate the user. This should be in the next line. "
            "The post should be concise, informative, and suitable for a professional audience. "
            "It should provide value, insights, or thought-provoking content related to the topic. "
            "And only contain 3 points. "
            
        )
        if radio == "Open AI":  # Corrected if statement syntax and comparison
           # generate_openai_post(role, temp)
            llm = OpenAI(temperature=temp, openai_api_key=st.secrets["OPENAI_API_KEY"])  # Corrected variable name
            response = llm(prompt)
    return response
            
    
        elif radio == "Gemini":
        #generate_gemini_post(role, temp)
        llm = ChatGoogleGenerativeAI(model="gemini-pro")
        result = llm.invoke(prompt)
    return print(result.content)

     """"       
    if radio == "Open AI":  # Corrected if statement syntax and comparison
        generate_openai_post(role, temp)
    
    elif radio == "Gemini":
        generate_gemini_post(role, temp)

def generate_openai_post(role, temp):
   def generate_linkedin_post(topic, role):
        # Enhanced prompt with additional context for better post generation
        prompt = (
            f"You as {role} Create a professional, engaging LinkedIn post about {topic}. "
            f"Adjust the tone and style based on a temperature of {temp}. " 
            "It should start with an attention grabbing hook based on audience pain. "
            "Then a line to agitate the user. This should be in the next line. "
            "The post should be concise, informative, and suitable for a professional audience. "
            "It should provide value, insights, or thought-provoking content related to the topic. "
            "And only contain 3 points. "
            
        )
        llm = OpenAI(temperature=temp, openai_api_key=st.secrets["OPENAI_API_KEY"])  # Corrected variable name
        response = llm(prompt)
        return response
    
    with st.form("my_form"):
        topic = st.text_area("Enter the topic for your LinkedIn post:")
        submitted = st.form_submit_button("Generate Post")
        if submitted and topic:
            post = generate_linkedin_post(topic, role)
            st.info(post)
        elif submitted and not topic:
            st.error("Please enter a topic to generate a post.")

def generate_gemini_post(role, temp):
    prompt = (
            f"You as {role} Create a professional, engaging LinkedIn post about {topic}. "
            f"Adjust the tone and style based on a temperature of {temp}. " 
            "It should start with an attention grabbing hook based on audience pain. "
            "Then a line to agitate the user. This should be in the next line. "
            "The post should be concise, informative, and suitable for a professional audience. "
            "It should provide value, insights, or thought-provoking content related to the topic. "
            "And only contain 3 points. "
            
        )
    llm = ChatGoogleGenerativeAI(model="gemini-pro")
    result = llm.invoke(prompt)
    return print(result.content)
    # Call Gemini API functions to generate LinkedIn post
    # gemini.generate_linkedin_post(topic, role)
    st.error("Gemini API integration is not yet implemented.")
 """
if __name__ == "__main__":
    main()